SKILLEMALL.ai

AD im-framework

Forrest's Team — Immanent Metaphysics agent framework and onboarding. Use when: (1) reasoning from the IM framework (axioms, modalities, ICT, effective choice), (2) helping a team member set up their own OpenClaw agent, (3) configuring a soul file grounded in the IM, (4) engaging other agents with principled ethics, (5) connecting to the team ecosystem (Telegram bots, agent directory), (6) citing or paraphrasing Forrest Landry's work with proper attribution, (7) loading IM reference materials into an agent workspace, (8) answering questions about the team's agent network or onboarding process. Includes structured ontology (134 concepts, 348 relations), soul file template, attribution guidelines, and full setup guide.

modbender/skill-library-mcp Agent Skills author: modbender MIT 10 files body ≈ 1 166 tokens Open the sourcegithub.com analyzed 3 d ago

Forrest's Team — Immanent Metaphysics agent framework and onboarding.

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureTelegramAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
88
Run on models
none yet
Process rating
D
39/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Dangerous commands cmd-pipe-to-shell-known-host references/setup-guide.md:32
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 39/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (im-framework) differs from the folder (im-framework-team)
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 85Steps. 30 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 1166 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 726: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 30 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.